Applicability of estimating glomerular filtration rate equations in pediatric patients: comparison with a measured glomerular filtration rate by iohexol clearance


Deng, F.; Finer, G.; Haymond, S.; Brooks, E.; Langman, C.B.

Translational Research 165(3): 437-445

2015


Estimating glomerular filtration rate (eGFR) has become popular in clinical medicine as an alternative to measured GFR (mGFR), but there are few studies comparing them in clinical practice. We determined mGFR by iohexol clearance in 81 consecutive children in routine practice and calculated eGFR from 14 standard equations using serum creatinine, cystatin C, and urea nitrogen that were collected at the time of the mGFR procedure. Nonparametric Wilcoxon test, Spearman correlation, Bland-Altman analysis, bias (median difference), and accuracy (P15, P30) were used to compare mGFR with eGFR. For the entire study group, the mGFR was 77.9 ± 38.8 mL/min/1.73 m(2). Eight of the 14 estimating equations demonstrated values without a significant difference from the mGFR value and demonstrated a lower bias in Bland-Altman analysis. Three of these 8 equations based on a combination of creatinine and cystatin C (Schwartz et al. New equations to estimate GFR in children with CKD. J Am Soc Nephrol 2009;20:629-37; Schwartz et al. Improved equations estimating GFR in children with chronic kidney disease using an immunonephelometric determination of cystatin C. Kidney Int 2012;82:445-53; Chehade et al. New combined serum creatinine and cystatin C quadratic formula for GFR assessment in children. Clin J Am Soc Nephrol 2014;9:54-63) had the highest accuracy with approximately 60% of P15 and 80% of P30. In 10 patients with a single kidney, 7 with kidney transplant, and 11 additional children with short stature, values of the 3 equations had low bias and no significant difference when compared with mGFR. In conclusion, the 3 equations that used cystatin C, creatinine, and growth parameters performed in a superior manner over univariate equations based on either creatinine or cystatin C and also had good applicability in specific pediatric patients with single kidneys, those with a kidney transplant, and short stature. Thus, we suggest that eGFR calculations in pediatric clinical practice use only a multivariate equation.

Applicability
of
estimating
glomerular
filtration
rate
cro
ct
equations
in
pediatric
patients:
comparison
with
a
measured
glomerular
filtration
rate
by
iohexol
clearance
FANG
DENG,
GAL
FINER,
SHANNON
HAYMOND,
ELLEN
BROOKS,
and
CRAIG
B.
LANGMAN
CHICAGO,
IL;
AND
HEFEI,
CHINA
Estimating
glomerular
filtration
rate
(eGFR)
has
become
popular
in
clinical
medi-
cine
as
an
alternative
to
measured
GFR
(mGFR),
but
there
are
few
studies
comparing
them
in
clinical
practice.
We
determined
mGFR
by
iohexol
clearance
in
81
consecutive
children
in
routine
practice
and
calculated
eGFR
from
14
stan-
dard
equations
using
serum
creatinine,
cystatin
C,
and
urea
nitrogen
that
were
collected
at
the
time
of
the
mGFR
procedure.
Nonparametric
Wilcoxon
test,
Spearman
correlation,
Bland-Altman
analysis,
bias
(median
difference),
and
accu-
racy
(P15,
P30)
were
used
to
compare
mGFR
with
eGFR.
For
the
entire
study
group,
the
mGFR
was
77.9
±
38.8
mL/min/1.73
m
2
.
Eight
of
the
14
estimating
equations
demonstrated
values
without
a
significant
difference
from
the
mGFR
value
and
demonstrated
a
lower
bias
in
Bland-Altman
analysis.
Three
of
these
8
equations
based
on
a
combination
of
creatinine
and
cystatin
C
(Schwartz
et
al.
New
equa-
tions
to
estimate
GFR
in
children
with
CKD.
J
Am
Soc
Nephrol
2009;20:629-37;
Schwartz
et
al.
Improved
equations
estimating
GFR
in
children
with
chronic
kidney
disease
using
an
immunonephelometric
determination
of
cystatin
C.
Kidney
Int
2012;82:445-53;
Chehade
et
al.
New
combined
serum
creatinine
and
cystatin
C
quadratic
formula
for
GFR
assessment
in
children.
Clin
J
Am
Soc
Nephrol
2014;9:54-63)
had
the
highest
accuracy
with
approximately
60%
of
P15
and
80%
of
P30.
In
10
patients
with
a
single
kidney,
7
with
kidney
transplant,
and
11
additional
children
with
short
stature,
values
of
the
3
equations
had
low
bias
and
no
significant
difference
when
compared
with
mGFR.
In
conclusion,
the
3
equations
that
used
cystatin
C,
creatinine,
and
growth
parameters
performed
in
a
superior
manner
over
univariate
equations
based
on
either
creatinine
or
cystatin
C
and
also
had
good
applicability
in
specific
pediatric
patients
with
single
kidneys,
those
with
a
kidney
transplant,
and
short
stature.
Thus,
we
suggest
that
eGFR
calculations
in
pe-
diatric
clinical
practice
use
only
a
multivariate
equation.
(Translational
Research
2015;165:437-445)
Abbreviations:
BUN
=
blood
urea
nitrogen;
eGFR
=
estimated
glomerular
filtration
rate;
mGFR
=
measured
glomerular
filtration
rate;
Scr
=
serum
creatinine;
Scys
=
serum
cystatin
C
From
the
Division
of
Kidney
Diseases,
Department
of
Pediatrics,
Feinberg
School
of
Medicine,
Northwestern
University,
Chicago,
Ill;
Division
of
Kidney
Diseases,
Department
of
Pediatrics,
Ann
and
Robert
H
Lurie Children's
Hospital
of
Chicago,
Chicago,
Ill;
Department
of
Pediatrics,
First
Affiliated
Hospital
of
Anhui
Medical
University,
Hefei,
Anhui
Province,
China;
Department
of
Pathology
and
Laboratory Medicine,
Ann
and
Robert
H
Lurie
Children's
Hospital
of
Chicago,
Chicago,
111;
Department
of
Pathology
and
Laboratory
Medicine,
Feinberg
School
of
Medicine,
Northwestern
University,
Chicago,
Ill.
Submitted
for
publication
July
3,
2014;
revision
submitted
October
6,
2014;
accepted
for
publication
October
8,
2014.
Reprint
requests:
Craig
B.
Langman,
Kidney
Diseases,
Ann
and
Robert
H.
Lurie
Children's
Hospital
of
Chicago,
225
E
Chicago
Avenue,
#37
Chicago,
IL
60611; e-mail:
1931-5244/$
-
see
front
matter
©
2015
Elsevier
Inc.
All
rights
reserved.
http://dx.doi.org/10.1016/j.trs1.2014.10.004
437
Translational
Research
438
Deng
et
al
March
2015
AT
A
GLANCE
COMMENTARY
Deng
F,
et
al.
Background
There
are
many
estimating
glomerular
filtration
rate
(GFR)
equations
used
in
clinical
practice.
The
bedside
CKiD
formula,
based
on
creatinine
only,
is
the
most
widely
used
formula
in
children.
However,
recent
studies
mainly
in
adults
demon-
strated
that
a
combination
of
creatinine
and
cysta-
tin
C
has
superior
performance.
Few
studies
have
evaluated estimating
GFR
equations in
pediatric
patients.
Translational
Significance
This
study
translated
the
field
of
laboratory
medi-
cine
for
determining
kidney
function
in
children
into
an
improved
standard
of
clinical
practice,
by
calculating
the
accuracy
of
multiple
estimating
equations
through
careful
analysis
of
correlations'
accuracy.
When
applied
in
2
special
populations,
we
found
3
equations
to
remain
robust
when
compared
with
measured
GFR.
INTRODUCTION
The
glomerular
filtration
rate
(GFR)
is
considered
the
best
overall
index
of
kidney
function
in
health
and
dis-
ease.
Thus,
accurate
measured
GFR
(mGFR)
plays
an
important
role
in
the
clinical
management
of
various
diseases,
both
intrinsic
to
the
kidney
and
with
other
dis-
eases
in
which
altered
kidney
function
may
influence
the
use
of
therapeutic
agents,
for
example.
More
than
80%
of
clinical
laboratories
now
report
an
estimating
GFR
(eGFR)
when
serum
creatinine
(Scr)
is
measured!
However,
in
recent
years
there
are
many
studies
that
have
shown
that
eGFR
equations
using
additional markers
of
filtration,
such
as
cystatin
C,
are
superior
to
conventional
equations
based
on
Scr
alone
2
.3
These
equations
were
tested
mainly
in
adult
patients
with
chronic
kidney
disease
(CKD),
whereas
only
a
few
studies
have
evaluated
performance
of
eGFR
equations
in
pediatric
CKD
outside
a
research
setting.
The
most
popular
equation
currently
used
in
children
is
the
2009
Schwartz
formula,
which
is
based
on
Scr.
4
Despite
standardization
of
Scr
assays,
eGFR
remains
relatively
imprecise
owing
to
variation
in
non-GFR
de-
terminants
of
Scr.
5
This
equation
does
not
differentiate
between
gender,
despite
the
known
gender
difference
in
linear
height
and
Scr
concentrations,
beginning
in
early
adolescence.
Thus,
such
anthropometric
disparities
result
in
a
considerable
variation
in
muscle
mass
and
may
be
a
dominant
factor
in
eGFR
differences.
6
Some
studies
in
children
have
demonstrated
that
the
inclusion
of
serum
cystatin
C
(Scys)
in
the
estimating
equation
in-
creases
the
correlation
with
the
mGFR
than
Scr
alone.
7
'
8
We
compared
14
published
eGFR
equations
against
a
gold
standard
mathematical
model
for
mGFR
from
iohexol
blood
clearance
9
to
guide
clinicians
in
optimal
eGFR
determinations
in
a
diverse
group
of
children
with
possible
kidney
dysfunction.
We
hypothesized
that
the
complex
equation
using
gender,
height,
Scr,
and
Scys
may
be
highly
predictive
of
mGFR.
METHODS
Study
design
and
data.
This
study
was
conducted
at
the
Ann
and
Robert
H.
Lurie
Children's
Hospital
of
Chicago,
Illinois
(Lurie
Children's),
from
November
2012
to
January
2014.
We
used
a
single
cross-sectional
data
set
from
81
consecutive
outpatients
in
which
iohexol-based
mGFR
was
calculated,
based
on
the
model
used
by
Schwartz
et
al
from
the
Chronic
Kidney
Disease
in
Children
(CKiD)
study,
9
and
for
which
we
are
a
participating
center.
At
the
time
of
the
patient's
mGFR
study,
additional
data
collected
included
Scr,
Scys,
blood
urea
nitrogen,
visit
date,
anthropometrics,
and
demographics.
We
calculated
height-for-age
Z-score
according
to
the
United
States
Centers
for
Disease
Control
standards
of
recumbent
length
Z-scores,
birth
to
24
months,
and
stature
Z-scores,
2-20
years
in
centimeters,
by
gender
and
age!
°
Fourteen
eGFR
equations
were
included
and
their
respective
values
for
81
patients
were
compared
against
the
mGFRs.
This
retrospective
study
was
approved
by
the
Lurie
Children's
Hospital
of
Chicago
Institutional
Review
Board.
Laboratory
analyses.
We
measured
iohexol
in
serum
by
a
validated
liquid
chromatography
tandem
mass
spectroscopy
method
from
4
serial
blood
samples
collected
at
10,
30,
120,
and
300
minutes
postiohexol
injection
with
the
clearance
calculated
using
the
concen-
tration
of
iohexol
as
a
function
of
time
in
2
curves
(fast
and
slow
plasma
disappearance).
9
Scr
was
measured
using
an
isotope-dilution
mass
spectrometry
(IDMS)-
traceable
enzymatic
method
on
the
Roche
Cobas
6000,
following
the
Food
and
Drug
Administration
cleared
procedure
for
Roche
or
Hitachi
Cobas
C
systems.
Blood
urea
nitrogen
and
cystatin
C
were
analyzed
in
serum
on
the
Roche
Cobas
6000,
following
the
Food
and
Drug
Administration
cleared
procedures
for
Roche
or
Hitachi
Cobas
C
systems.
The
cystatin
C
method
on
the
Roche
Cobas
6000
uses
an
automated
particle-enhanced
immunoturbidimetric
assay
(PETIA).
rranslational
Research
Volume
165,
Number
3
Deng
et
al
439
Table
I.
Published
estimated
glomerular
filtration
rate
equations
in
children
Equation
name
Equation
Scr
based
Schwartz
et
a1
4
(ScrEq2009)
Schwartz
et
a1
11
(ScrEq2012)
Gao
et
a1
12
Pottel
et
al
13
Hoste
et
a15
Scys
based
Bokenkamp
et
a1
14
Grubb
et
a1
15
Filler
and
Lepage
l6
Schwartz
et
a1
4
(ScysEq2009)
Schwartz
et
a1
11
(ScysEq2012)
Scr
and
Scys
based
Bouvet
et
a1
17
Schwartz
et
al.
4
(ScrcysEq09)
Schwartz
et
a1
11
(ScrcysEq12)
Chehade
et
a1
18
41.3Ht/Scr
42.3(Ht/Scr)
°.79
68(Ht/Scr)
-
8(Ht/Scr)
2
+
0.48
x
age
-
21.53
in
males
or
25.68
in
females
107.3/(Scr/Q),
Q
=
0.0270
x
age
+
0.2329
107.3/(Scr/Q),
Q
=
3.94
-
13.4
L
+
17.6
L
2
-
9.84
L
3
+
2.04
L
4
(162/Scys)
-
30
84.69Scys
-1.68
x
1.384
for
age
<14
years
91.62(1/Scys)
1
123
41
.9(1
.8/SCYS)
C).777
70.69Scys
-0931
63.2(1.2/Scys)
a56
(1.09/Scr)"
5
(weight/45)"
(age/14)
0A
39.1
(Ht/Scr)
°
516
(1.8/Scys)
°294
(30/BUN)
°.169
1.099
maie
(Ht/1.4)
0188
39.8
(Ht/Scr)
°A56
(1.8/Scys)
°A-18
(30/BUN)
a°79
1.076
mal°
(Ht/1.4)
0.17°
42(Ht/Scr)
-
4(Ht/Scr)
2
-
14.5Scys
+
0.69age
+
18.25
for
female
or
21.88
for
male
Abbreviations:
BUN,
blood
urea
nitrogen
(in
mg/dL);
Ht
or
L,
height
(in
m);
Scr,
serum
creatinine
(in
mg/dL);
Says,
serum
cystatin
C
(in
mg/L).
Age
is
in
years;
weight
is
in
kilograms.
eGFR
calculation
formulas.
A
total
of
14
eGFR
equa-
tions
were
selected
to
calculate
eGFR
(Table
I).
These
include
5
equations
based
on
Scr
alone,
5
based
on
Scys
alone,
and
4
based
on
combinations
of
both.
The
method
of
testing
Scys
was
particle-enhanced
nephelometric
immunoassay
(PENIA)
in
Filler
et
a1,
16
Bouvet
et
a1,
17
Chehade
et
a1,
18
and
Schwartz
et
a1
4.11
equations.
The
others
used
the
PETIA
method.
The
method
of
testing
Scr
was
Jaffe
method
in
Gao
et
al,
Bouvet
et
al,
and
Chehade
et
al
equations.
The
others
used
the
enzymatic
assay.
Statistical
analyses.
Continuous
data
were
described
as
the
mean
±
standard
deviation,
median,
and
inter-
quartile
range
(IQR),
and
categorical
variables
were
ex-
pressed
as
cases
or
percentages.
Differences
between
eGFR
and
mGFR
were
analyzed
by
the
nonparametric
Wilcoxon
test,
because
the
data
were
not
normally
distributed.
Correlations
between
eGFR
and
mGFR
were
established
based
on
the
Spearman
correlation.
Bland-Altman
analysis
was
used
to
compare
eGFR
with
mGFR
using
the
average
of
the
overall
mean
±
standard
deviation
and
the
precision
was
represented
as
the
width
between
the
95%
limits
of
agreement,
wherein
the
smaller
the
limits
of
agreement,
the
greater
the
precision.
Regression
analysis
and
scatterplot
analysis
were
used
to
compare
the
agreement
between
eGFR
and
mGFR.
Three
parameters
used
to
assess
the
performance
of
eGFR
equations
relative
to
mGFR
were
as
follows:
Bias
(median
difference
between
mGFR
and
eGFR)
and
absolute
bias
(median
difference
in
ImGFR
-
eGFRI;
precision
(IQR:
P75-P25);
and
accuracy
[percentage
of
estimates
that
differed
within
15%
of
mGFR
(P
15
)
and
30%
of
mGFR
(P313)].
We
selected
P
<
0.05
a
priori
to
be
statistically
signif-
icant.
Statistical
analyses
were
completed
using
Statis-
tic
Package
for
Social
Science
(SPSS,
Inc,
Chicago,
Illinois)
and
Medcalc
(Medcalc
Software,
Mariekerke,
Belgium).
RESULTS
Demographic
and
clinical
characteristics.
Characteristics
of
interest
for
our
study
population
of
81
children
and
ad-
olescents
are
shown
in
Table
II.
The
minimum
and
maximum
ages
of
the
participants
were
0.70
and
20
years,
respectively.
There
were
10
patients
with
single
kidney
and
7
with
a
kidney
transplant.
The
primary
diseases
that
resulted
in
a
kidney
transplant
were
nephropathic
cystinosis
(4
cases),
kidney
dysplasia
(2
cases),
and
autosomal
recessive
polycystic
kidney
disease
(1
case).
Five
patients
with
Wilms
tumor,
1
with
mesoblastic
nephroma,
and
1
with
Langer
Giedion
syndrome
had
single
native
kidneys
after
a
unilateral
nephrectomy
performed
for
clinical
care.
Analysis
of
the
differences
between
the
eGFR
and
mGFR
values.
The
values
of
mGFR
and
the
14
corresponding
eGFR
values
are
shown
in
Table
DI.
The
mean
mGFR
for
the
81
subjects
was
77.9
±
38.8
mL/min/1.73
m
2
.
The
median
and
IQR
(P25,
P75)
were
77.8,
52.0,
and
96.0
mL/min/1.73
m
2
,
respectively.
The
numbers
of
patients
with
mGFR
.
90,
60-89,
30-59,
and
<30
mL/min/1.73
m
2
were
25,
31,
17,
and
8,
Translational
Research
440
Deng
et
al
March
2015
Table
II.
Characteristics
of
study
participants
Variable
Value
Measured
glomerular
filtration
rate
test,
n
Age,
y
Mean
±
standard
deviation
12.60
81
±
5.14
Median
(P
25
,1
0
75
)
14.29
(8.96,
16.88)
Gender,
n
(%)
Female
37
(45.7)
Male
44
(54.3)
Ethnicity/race,
n
(%)
White
47
(58.0)
Hispanic
22
(27.2)
Black
10
(12.3)
Asian
2
(2.5)
Weight
(kg),
median
(P
25
,
P
75
)
46.30
(29.05,
60.40)
Height
(cm)
Median
(P
25
,1
0
75
)
152.30
(124.70,
167.60)
Z-score
—0.77
±
1.97
Single
kidney,
n
(%)
Native
kidney
3
(3.7)
After
nephrectomy
7
(8.6)
2
Kidneys,
n
(%)
64
(79.0)
Kidney
transplantation,
n
(%)
7
(8.6)
Primary
kidney
disease,
n
(%)
Congenital
anomalies
of
the
kidney
and
urinary
tract
16
(19.7)
Glomerular
disease
6
(7.4)
Tubulointerstitial
disease
5
(6.2)
Solid
organ
transplantation
other
than
kidney
17
(21.0)
Metabolic
disease
23
(28.4)
Other
14
(17.3)
Abbreviations:
FSGS,
Focal
Segmental
Glomerular
Sclerosis;
p-ANCA,
perinuclear
anti-neutrophil
cytoplasmic
antibody;
STEC-HUS,
shiga
toxin
escherichia
coli
hemolytic
uremic
syndrome.
Glomerulopathies
include
6
patients
with
microscopic
polyangiitis,
congenital
nephrotic
syndrome,
thin
basement
membrane,
FSGS,
Kawasaki
disease,
and
p-ANCA
positive
microscopic
polyangiitis,
respectively.
Tubulointerstitial
disease
includes
5
patients
with
renal
tubular
acidosis,
type
I,
Fanconi
syndrome,
interstitial
nephritis,
Bart-
ter
syndrome,
and
acute
tubular
necrosis,
respectively.
Solid
organ
transplantation
other
than
kidney
includes
patients
with
a
trans-
plant
of
the
liver
(13),
heart
(1),
lung
(2),
and
bone
marrow
(1).
Metabolic
disease
includes
cystinosis
(5),
nephrolithiasis
or
hyper-
calciuria
(12),
and
6
patients
with
Hashimoto's
thyroiditis,
Lennox-
Gastaut
syndrome,
tuberous
sclerosis,
Mainzer-Saldino
syndrome,
Langer
Giedion
syndrome,
methylmalonic
academia,
respec-
tively.
"Other"
are
5
patients
with
Wilms
tumor,
3
with
renovascular
disease,
4
with
mesoblastic
nephroma,
STEC-HUS
and
diabetes
mellitus,
autosomal
recessive
polycystic
kidney
disease,
and
neuro-
fibromatosis,
respectively,
and
2
with
unknown
etiology
of
chronic
kidney
disease.
respectively.
The
calculated
eGFR
values
were
highly
correlated
(P
<
0.001)
with
the
mGFR
value.
However,
3
equations
based
on
Scr
alone,
1
based
on
Scys,
and
all
4
based
on
combinations
of
both
demonstrated
no
significant
difference
from
the
mGFR
values
(P
>
0.05).
These
same
8
equations
also
had
lower
bias
compared
with
the
others
in
the
Bland-Altman
analysis.
Consistency
analysis
of
the
eGFR
and
mGFR
values.
Table
IV
lists
the
performance
of
the
selected
8
equations
determined
by
calculating
accuracy,
bias,
and
precision.
All
had
low
bias,
but
3
multivariate
equations
based
.
on
a
combination
of
Scr
and
Scys,
Schwartz
et
al
and
Chehade
et
al
had
the
highest
accuracy
with
approximately
60%
of
P15
and
80%
of
P30.
Fig
1
shows
the
agreement
between
eGFR
and
mGFR
for
these
3
multivariate
equations.
There
was
good
agreement
across
the
GFR
range
from
low
to
high,
espe-
cially
for
equations
of
Schwartz
et
a1.
4
Analysis
of
the
differences
between
the
multivariate
equation
and
mGFR
in
patients
with
single
kidney,
kidney
transplant,
or
short
stature.
On
the
basis
of
the
results
mentioned
previously,
the
3
multivariate
equations
had
the
best
performance
among
all
eGFR
equations.
We
analyzed
their
applicability
in
10
patients
with
a
single
kidney,
7
with
kidney
transplant,
and
11
short
stature
pa-
tients
with
height
Z-score<
---2.5
(Table
V).
From
the
Wilcoxon
test,
there
was
no
significant
difference
between
eGFR
and
mGFR
in
patients
with
single
kidney,
kidney
transplant,
and
short
stature
(P
0.05).
The
values
of
the
3
equations
also
showed
acceptable
bias
and
precision
in
the
Bland-Altman
analysis.
DISCUSSION
Accurate
assessment
of
GFR
is
essential
for
interpret-
ing
the
symptoms,
signs,
and
laboratory
abnormalities
that
may
indicate
kidney
disease,
for
monitoring
side
ef-
fects
of
therapeutic
drug
use,
and
for
detecting
and
man-
aging
CKD
and
assessing
its
prognosis,
among
others.
The
gold
standard
for
measuring
GFR
was
inulin
clear-
ance
for
many
years
and
was
performed
by
loading
and
continuously
infusing
inulin
and
collecting
timed
urine
samples
from
an
indwelling
bladder
catheter,
a
proce-
dure
very
cumbersome
and
difficult
to
perform
in
chil-
dren.
19
Iohexol
has
been
used
as
a
satisfactory
marker
of
GFR
in
adults
and
children,
based
on
its
ready
avail-
ability,
exclusive
elimination
by
the
kidneys
without
further
metabolism,
and
good
agreement
with
inulin
and
51Cr-EDTA
clearances.
Indeed,
iohexol
has
been
heralded
as
the
new
gold
standard
measure
of
GFR
and
especially
in
children.
In
the
present
study,
8
of
the
14
eGFR
equations
eval-
uated
demonstrated
better
performance
than
the
others
compared
with
mGFR.
These
8
were
a
mix
of
equations
based
on
Scr
only
(3/5),
Scys
only
(1/5),
and
a
combina-
tion
of
both
Scr
and
Scys
(4/4).
Further
analysis
demon-
strated
that
only
3
specific
multivariate
equations
had
better
performance
than
the
univariate
ones.
These
3
equations
all
included
Scr,
Scys,
gender,
and
a
statural
growth
parameter.
When
used
in
unique
patient
rranslational
Research
Volume
165,
Number
3
Deng
et
al
441
Table
Ill.
Overall
limits
of
agreement
between
eGFR
and
mGFR
Equation
name
Mean
±
SD
Wilcoxon
test
Correlation
analysis
Bland-Altman
analysis
r
P
Bias
95%
LOA
mGFR
77.9
±
38.8
- - -
_
-
Schwartz
et
ai
l
(ScrEq09)
83.4
±
48.5
-1.476
0.14
0.77
<0.001
-5.5
±
26.0
-56.5;
45.5
Schwartz
et
al"
(ScrEq12)
71.2
±
30.7
-2.229
0.03
0.77
<0.001
5.7
±
20.0
-33.5;
44.9
Gao
et
al
12
76.4
±
36.8
-1.490
0.14
0.73
<0.001
1.5
±
50.0
-96.5;
99.5
Pottel
et
al
13
85.1
±
44.5
-1.923
0.054
0.72
<0.001
-7.2
±
26.4
-58.9;
44.5
Hoste
et
al
b
84.9
±
46.2
-2.281
0.02
0.78
<0.001
-7.0
±
24.1
-54.2;
40.2
Bokenkamp
et
a1
14
126.5
±
64.0
-7.573
0.00
0.81
<0.001
-48.7
±
40.4
-127.9;
30.5
Grubb
et
a1
15
111.8
±
81.3
-5.412
0.00 0.80
<0.001
-33.9
±
54.6
-140.9;
73.1
Filler
and
Lepage
l6
94.1
±
42.6
-5.605
0.00
0.84
<0.001
-16.3
±
24.3
-63.9;
31.3
Schwartz
et
a1
4
(ScysEq09)
65.9
±
21.1
-3.962
0.00
0.84
<0.001
12.0
±
24.6
-36.2;
60.2
Schwartz
et
al
l
'
(ScysEq12)
71.2
±
27.0
-1.937
0.053
0.84
<0.001
6.6
±
22.5
-37.5;
50.7
Bouvet
et
al
l
'
73.9
±
31.1
-0.506
0.61
0.73
<0.001
3.9
±
28.3
-51.6;
59.4
Schwartz
et
a!
4
(ScrcysEq09)
77.9
±
32.3
-0.445
0.66
0.87
<0.001
-0.0
±
16.5
-32.3;
32.3
Schwartz
et
al
l
'
(ScrcysEq12)
76.2
±
30.8
-0.186
0.85
0.88
<0.001
1.7
±
16.6
-30.8;
34.2
Chehade
et
al
18
74.4
±
28.1
-0.308
0.76
0.79
<0.001
3.4
±
31.2
-57.8;
64.6
Abbreviations:
eGFR,
estimated
glomerular
filtration
rate;
95%
LOA,95%
limits
of
agreement;
mGFR,
measured
glomerular
filtration
rate;
r,
Spear-
man's
correlation
coefficient
between
eGFR
and
mGFR;
SD,
standard
deviation;
7,
value
of
the
Wilcoxon
test
between
eGFR
and
mGFR.
The
unit
of
GFR
is
mL/min/1.73
m
2
.
The
italicized
rows
are
equations
for
which
there
is
no
significant
difference
between
eGFR
and
mGFR
in
the
Wilcoxon
test.
Table
IV.
Performance
of
the
8
equations
in
the
overall
sample
Bias
Precision
Accuracy
(%)
Equation
name
Median
IQR
(P25,
P75)
Absolute
bias
Pis
P
so
Schwartz
et
a1
4
(ScrEq09)
-3.1
27.1
(-16.6,
10.5)
14.0
39.5
65.4
Gao
et
a1
12
-2.9
25.4
(-16.7,
8.7)
11.5
51.9
71.6
Pottel
et
a1
13
-3.1
27.2
(-18.5,
8.7)
13.9
44.4
64.2
Schwartz
et
al
l'
(ScysEq12)
1.9
19.6
(-5.0,
14.6)
8.6
53.1
79.0
Bouvet
et
al
l'
-0.2
30.1
(-14.0,
16.1)
15.2
34.6
64.2
Schwartz
et
ai
l
(ScrcysEq09)
-2.5
18.4
(-9.8,
8.6)
9.3
58.0
79.0
Schwartz
et
al
l
'
(ScrcysEq12)
-2.3
18.6
(-8.8,
9.8)
9.2
61.7
82.7
Chehade
et
al
18
0.7
19.9
(-10.1,
9.8)
9.9
59.3
77.8
Abbreviations:
eGFR,
estimated
glomerular
filtration
rate;
IQR,
interquartile
range;
mGFR,
measured
glomerular
filtration
rate;
SD,
standard
de-
viation.
Bias
was
the
median
difference
between
eGFR
and
mGFR
(mGFR
-
eGFR);
absolute
bias
was
I(mGFR
-
eGFR)I;
accuracy
was
calculated
as
the
percentage
of
estimates
of
eGFR
that
differed
from
the
mGFR
within
15%
(P
15
)
and
within
30%
(P
30
).
The
italicized
rows
are
the
equations
with
the
highest
accuracy.
populations
(ie,
those
with
single
kidney,
kidney
trans-
plant,
and
short
stature),
the
3
equations
demonstrated
high
agreement
with
mGFR.
There
are
only
a
few
studies
that
have
compared
the
applicability
of
eGFR
equations
based
on
different
included
variables
in
children.
The
performance
of
Scr-based
equations
was
studied
in
several
arti-
cles.
6.12.13
The
bedside
CKiD
formula
(Schwartz
et
a1
4
)
is
the
most
widely
used
formula
for
eGFR
in
chil-
dren.
However
it
was
derived
from
data
obtained
in
chil-
dren
with
CKD
mGFR between
15
and
75
mL/min/
1.73
m
2
.
Several
recent
studies
validated
new
Scr-
based
formulas
for
children,
which
all
outperformed
the
bedside
CKiD
formula
compared
with
inGFR.6,12,13
Sharma
et
a1
21
studied
several
Scys-
based
equations
and
found
the
accuracy
of
various
Scys
equations
varied
with
the
actual
mGFR.
In
a
study
focused
on
children
with
a
solitary
functioning
kidney,
the
authors
used
6
eGFR
equations
based
on
Scr,
Scys,
and
a
combination
of
both
variables,
and
found
the
combined
formula,
Schwartz
et
a1,
11
had
superior
precision.
22
For
clinical
practice,
we
need
to
identify
the
most
accurate
eGFR
equation
that
can
be
applied
to
a
diverse
pediatric
patient
population.
In
adults,
there
are
several
large
studies
capable
of
validating
the
accu-
racy
of
eGFR
equations.
One
recent
example,
the
Chronic
Kidney
Disease
Epidemiology
Collaboration,
developed
an
equation
based
on
Scr
in
2009
and
2
others
Translational
Research
442
Deng
et
al
March
2015
Table
V.
Agreements
between
multivariate
equations
and
mGFR
in
special
patients
Special
patient
Mean
±
SD
Wilcoxon
test
Bland-Altman
analysis
z
P
Bias
95%
LOA
Single
kidney
(n
=
10)
mGFR
66.5
±
19.2
Schwartz
et
a1
4
(ScrcysEq09)
77.3
±
22.0
-1.988
0.05
-10.8
±
14.5
-39.2;
17.6
Schwartz
et
al
l '
(ScrcysEq12)
75.0
±
20.5
-1.682
0.09
-8.5
±
13.6
-35.2;
52.2
Chehade
et
a1
l8
77.5
±
21.2
-1.988
0.05
-11.0
±
15.3
-41.0;
19.0
Kidney
transplant
(n
=
7)
mGFR
63.0
±
18.6
Schwartz
et
a1
4
(ScrcysEq09)
58.2
±
18.1
-0.676
0.50
4.8
±
12.5
-19.7;
29.3
Schwartz
et
al
l '
(ScrcysEq12)
57.5
±
17.5
-1.014
0.31
5.4
±
12.1
-18.3;
29.1
Chehade
et
a1
l8
57.9
±
24.3
-0.845
0.40
5.0
±
14.0
-22.4;
32.4
Z-score
(n
=
11)
mGFR
59.7
±
28.5
Schwartz
et
al'
(ScrcysEq09)
61.4
±
20.8
-0.445
0.66
-1.7
±
14.9
-30.9;
27.5
Schwartz
et
al
(ScrcysEq12)
59.8
±
19.6
-0.445
0.66
-0.1
±
14.7
-28.9;
28.7
Chehade
et
al
64.7
±
29.8
-0.978
0.33
-4.9
±
19.0
-42.1;
32.3
Abbreviations:
eGFR,
estimated
glomerular
filtration
rate;
95%
LOA,
95%
limits
of
agreement;
mGFR,
measured
glomerular
filtration
rate;
SD,
standard
deviation;
7,
value
of
the
Wilcoxon
test
between
eGFR
and
mGFR.
The
unit
of
GFR
is
mL/min/1.73
m
2
.
in
2012
(based
on
Scys
alone
and
combined
creatinine-
cystatin
C).
They
tested
the
3
equations
in
very
diverse
populations
with
CKD
and
normal
kidney
function
and
found
the
combined
creatinine-cystatin
C
equation
per-
formed
better
than
equations
based
on
either
of
both
markers
alone
when
compared
with
mGFR.
2
The
com-
bined
equation
is
commonly
used
in
adult
hospitals
as
the
method
for
eGFR
in
adults,
replacing
the
popular
Modification
of
Diet
in
Renal
Disease
eGFR.
3.23
Similarly
to
others
in
adults
and
children,
we
found
that
all
3
combined
(Scr
with
Scys)
equations
outperformed
equations
that
used
the
Scr
or
Scys
alone.
Cystatin
C
is
freely
filtered
and
catabolized
in
the
proximal
tubules,
without
being
secreted.
Unlike
Scr,
it
does
not
depend
on
gender
or
muscle
mass
and
does
not
change
with
age
between
1
and
50
years
old.
24
Scys
increases
earlier
than
Scr
as
GFR
decreases,
so
it
may
be
a
valuable
marker
in
detecting
early
renal
dysfunction.
25.26
In
an
early
meta-analysis,
Scys
has
also
been
reported
to
be
superior
to
Scr
for
GFR
estima-
tion,
particularly
in
patients
with
near-normal
kidney
function.
27
In
addition
to
its
use
in
estimating
GFR,
cys-
tatin
C
has
also
been
associated
with
subsequent
adverse
clinical
events.
In
prior
studies
in
the
general
population
and
in
the
elderly,
cystatin
C
has
been
shown
to
be
a
bet-
ter
predictor
of
mortality
and
adverse
cardiovascular
events
than
Scr
alone.
28-3°
Peralta
et
a1
31
studied
cysta-
tin
C
level
in
11,909
participants
and
found
its
level
may
have
a
role
in
identifying
individuals
with
CKD
who
have
the
highest
risk
for
complications.
The
addition
of
cystatin
C
may
improve
mortality
risk
prediction
by
stages
of
kidney
function
relative
to
Scr.
3
In
our
study,
all
3
combined
equations
with
Scys
exhibited
su-
perior
agreement
and
performance,
but
each
of
those
equations
also
included
patient
height
and
gender.
How-
ever,
including
the
height
and
gender
does
not
explain
totally
the
better
performance
of
eGFR
equations,
because
several
other
Scr-based
equations
used
those
variables
as
well.
It
is
well
known
that
a
gender
differ-
ence
in
the
correlation
of
growth
(height)
and
blood
Scr
concentration
exists
beginning
in
adolescence.
This
large
variation
in
body
shape
and
linear
height
de-
termines
extreme
variations
in
muscle
mass
and
may
be
a
dominant
factor
when
developing
eGFR
formulas
for
children,
teens,
and
young
adults.
6
Higher
cystatin
C
concentrations
have
been
found
in
the
first
year
of
life
previously.
Bokenkamp
et
a1
33
stud-
ied
Scys
level
in
258
children
without
kidney
disease,
aged
1
day
to
18
years,
and
found
the
cystatin
C
concen-
tration
was
highest
on
the
first
days
of
life
(range
1.64
±
2.59
mg/L)
with
a
rapid
decrease
during
the
first
4
months.
Beyond
the
first
year,
the
cystatin
C
concentra-
tion
was
constant.
In
a
more
recent
study,
Scys
level
was
found
to
be
a
superior
biomarker
to
Scr
in
the
assessment
of
GFR
in
premature
infants.
34
It
is
likely
that
the
higher
levels
of
cystatin
C
in
the
first
year
of
life
probably
reflect
the
low
GFR
of
neonates
and
infants.
In
our
study,
we
only
had
1
child
under
1
year
(0.7
years).
There
was
a
good
agreement
between
mGFR
and
eGFR
based
on
multivariate
Schwartz
equations.
It
should
be
noted
that
creatinine
and
cystatin
C
meth-
odologies
differ
among
the
various
equations
and
sys-
tematic
differences
in
measurement
could
contribute
to
the
accuracy
of
the
equations,
given
the
methods
Translational
Research
Volume
165,
Number
3
Deng
et
al
443
A
300.00
-
y=1.091x-7.143
300.00
-
r1.151x-9.779
al.979
-1.204
a=1.034
-1.267
b=-16.630
-
2.343
b=-19.314
-
-0.243
250.00
-
250.00
-
200.00
-
200.00
-
rc
150.00
-
LL
150.00
-
100.00
-
100.00
-
50.09
-
R
2
Linear
=0.825
50.00
-
R
2
Linear
=0.831
0.00
-
0.00
-
0.00
50.00
100.00 150.00
200.00 250.00
0.00
5000
106.00 150.00
20d.00
25d.00
ScrcysEq09
C
SercysEq12
300.00
-
y.1837x+15.546
a.590
-1.084
R
2
Linear
=0.366
b=-4.060
-
35.152
0
250.00
-
200.00
-
150.00
-
°
100.00
-
p
0
0
50.00
-
0
°
°
0.00
-
-20.00
0.00
20.00
40.00
60.00
80.00
10000
120.00
Chehade
Fig
1.
Scatterplot
regression
to
analyze
and
compare
eGFR
with
mGFR.
A,
Schwartz
et
a1
4
(ScrcysEq09)
eGFR
equation
explains
82.5%
of
the
variability
of
mGFR.
B,
Schwartz
et
a1
11
(ScrcysEq12)
eGFR
equation
explains
83.1%
of
the
variability
of
mGFR.
C,
Chehade
et
al
18
eGFR
equation
explains
36.6%
of
the
variability
of
mGFR.
'95%
CI
for
the
slope;
b
95%
CI
for
the
intercept;
all
P
<
0.001.
CI,
confidence
interval;
eGFR,
estimated
glomerular
filtration
rate;
mGFR,
measured
glomerular
filtration
rate.
used
in
the
present
report.
Because
the
relationship
of
both
creatinine
and
cystatin
C
to
GFR
is
exponential,
the
effect
of
analytical
error
(bias
and
precision)
will
be
greater
at
lower
or
"normal"
creatinine
values
(cor-
responding
to
high
GFR)
and
the
same
difference
will
have
minimal
impact
at
highly
abnormal
creatinine
values,
which
correspond
to
low
GFR.
Creatinine
assays
relying
on
both
the
Jaffe
and
enzymatic
methods
are
now
standardized
to
a
material
characterized
by
a
gold
standard
method,
IDMS-traceable
method.
Many
of
the
equations
evaluated
herein
used
an
enzymatic
IDMS-traceable
creatinine
method,
which
is
what
we
use
at
our
institution.
The
Gao
et
a1
12
Scr-only
equation
is
based
on
a
Jaffe
IDMS-traceable
method,
and
we
found
this
equation,
using
our
creatinine
values,
to
have
high
agreement
with
mGFR.
The
methodological
differences
noted
between
cysta-
tin
C
assays
lead
to
similar
limitations
that
were
histor-
ically
experienced
with
creatinine
and
various
eGFR
equations.
Efforts
are
now
underway
to
calibrate
different
cystatin
C
methods
to
a
single
traceable
refer-
ence
material.
The
first
report
of
a
virtually
assay-
independent
simple
cystatin
C-based
eGFR
equation
based
on
calibration
of
different
methods
to
an
interna-
tional
reference
material
was
recently
published.
35
In
the
present
study,
our
laboratory
used
a
PETIA
method
on
the
Roche
Cobas
6000
e501.
Most
of
the
equations
evaluated
reportedly
used
a
PENIA
method,
most
commonly
that
on
the
Siemens
Bulk
Nanocrystallized
Ingot
Iron
platform.
Hansson
et
a1
36
showed
in
a
com-
parison
of
180
patient
samples
that
Passing-Bablok
regression
analyses
yielded
a
slope
of
0.904
and
inter-
cept
of
0.21
with
regression
coefficient
of
0.9343
for
cystatin
C
measured
by
Roche
Cobas
e501
cystatin
C
PETIA
and
Siemens
Bulk
Nanocrystallized
Ingot
Iron
PENIA.
Despite
the
limitations
because
of
analytical
differences
among
methods,
we
have
shown
that
the
combination
of
creatinine
and
cystatin
C
improves
ac-
curacy
to
mGFR.
The
primary
strength
of
this
study
is
that
it
compares
performance
of
14
published
eGFR
equations
in
pediat-
ric
patients
evaluated
against
an
accurate
and
precise
mGFR
method
in
the
routine
clinical
setting.
The
effects
of
different
variables
in
the
eGFR
formulas
were
compared
using
a
rigorous
analytic
plan
to
test
the
for-
mulas
against
mGFR.
Different
analytic
methods
Translational
Research
444
Deng
et
al
March
2015
demonstrated
similar
results
for
performance
of
each
equation.
No
previous
study
has
specifically
assessed
the
comparison
of
these
comprehensive
equations
in
this
age
group.
The
limitations
of
this
study
include
a
relatively
small
sample
of
subjects,
and
the
analysis
was
not
based
on
CKD
stage,
owing
to
a
relatively
small
number
expected
in
some
groups.
However,
in
data
shown
from
the
scatterplot
regression
analyses,
a
stron-
ger
correlation
can
be
seen
with
worsening
CKD
stage
than
in
CKD
stage
1,
especially
for
the
2
Schwartz
multivariate
equations.
Alternatively,
the
high
overall
correlation
suggests
that
it
would
not
have
been
different
by
differing
stage
of
CKD
with
greater
patient
numbers
within
the
lower
bounds
of
mGFR.
CONCLUSIONS
The
multivariate
eGFR
equations
performed
in
a
supe-
rior
fashion
than
the
univariate
equations.
The
3
eGFR
formulas
based
on
a
combination
of
Scr,
Scys,
gender,
and
a
growth
parameter
(Schwartz
et
a1
4.11
and
Chehade
et
a1
18
)
demonstrated
exceptional
accuracy
among
all
formulas
and
had
good
applicability
in
special
patients
including
those
with
a
single
kidney,
kidney
transplant,
and
short
stature.
Adding
height
and
Scys
to
eGFR
formula
seems
to
be
important
in
improving
ac-
curacy
of
the
estimating
equation.
Our
data
suggest
that
for
best
accuracy
to
mGFR,
all
eGFR
calculations
in
pe-
diatric
clinical
practice
use
only
multivariate
equations,
particularly
1
of
the
3
mentioned
previously.
As
this
is
a
small
study,
our
recommendations
need
to
be
confirmed
in
a
larger
sample
size.
ACKNOWLEDGMENTS
Conflicts
of
Interest:
All
authors
have
read
the
jour-
nal's
policy
on
disclosure
of
potential
conflicts
of
inter-
est
and
have
none
to
declare.
The
study
was
supported
in
part
by
grants
from
the
National
Institutes
of
Health,
HD
074596-02,
DK666174,
and
DK083908-01
and
by
a
grant,
National
Science
Foundation
of
China,
NSFC
81302447
from
Dr
Deng's
hospital,
First
Affiliated
Hospital
of
Anhui
Med-
ical
University,
Hefei,
Anhui
Province,
China.
All
authors
have
read
the
journal's
authorship
agree-
ment.
The
manuscript
has
been
reviewed
and
approved
by
all
named
authors.
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